Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | 7B | 9B |
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 32k | 128k |
| Overview | ||
| Company | Mistral | Z.ai |
| Release date | Jul 16 2024 | Jun 5 2024 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Mathstral 7BvsClaude Haiku 5.5GLM-4-9BvsClaude Haiku 5.5Mathstral 7BvsGPT-6.1 SolGLM-4-9BvsGPT-6.1 SolMathstral 7BvsGemini 4 ArgonGLM-4-9BvsGemini 4 ArgonMathstral 7BvsMuse Spark OpenGLM-4-9BvsMuse Spark OpenMathstral 7BvsGrok 4.7GLM-4-9BvsGrok 4.7Mathstral 7BvsDeepSeek-V4.1-Flash-1017GLM-4-9BvsDeepSeek-V4.1-Flash-1017Frequently asked questions
Mathstral 7B and GLM-4-9B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. GLM-4-9B shipped 41 days before Mathstral 7B, so benchmark comparisons should account for the intervening progress.
Mathstral 7B has 7B parameters, while GLM-4-9B has 9B. Context windows are 32k (Mathstral 7B) vs 128k (GLM-4-9B).
Direct benchmark comparisons are unavailable — Mathstral 7B and GLM-4-9B don't publish scores on any of the same benchmarks.